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Application of grey model and ARIM multiple seasonal model in the prediction of brucellosis in Chengde of Heibei Province / 中华地方病学杂志
Chinese Journal of Endemiology ; (12): 338-340, 2018.
Article in Chinese | WPRIM | ID: wpr-701328
ABSTRACT
Objective The grey model [GM (1,1)] and the ARIMA multiple seasonal model were used to predict the incidence trend of brucellosis in Chengde,and the effects of predictions of the two models is compared.Methods According to the statistical results of epidemiological research results of monthly brucellosis patients in Chengde from 2008 to 2014,we established the ARIMA multiple seasonal model and GM (1,1) model,individually predicted the trend of brucellosis in 2015.Compared with the actual monitoring results,the average relative error was used to verify the reliability of the model.Results GM (1,1) model was (X)0(k) =0.001 6 (X)0 + 23 712.31) exp [0.001 6 (k-t0)],and the optimal model for determining the ARIMA multiple seasonal model of product was ARIMA (0,1,1) × (0,1,0)12.The average relative errors of the two models predicted in 2015 from January to December compared with the actual monitoring data were 114.82% and 11.66%.Conclusion The product ARIMA multiple seasonal model has better predictive effect on brucellosis,and can be used for short-term forecasting.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Endemiology Year: 2018 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Prognostic study Language: Chinese Journal: Chinese Journal of Endemiology Year: 2018 Type: Article